• Asian Pacific Journal of Cancer Prevention
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• v.13 no.3
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• pp.945-951
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• 2012

Objective: FAS/FASL gene promoter polymorphisms have been repeatedly associated with gastric cancer risk, but findings are inconclusive across studies. To address a more precise estimation of the relationship, a meta-analysis was performed. Methods: Data were collected from the Pubmed, Medline and EMBASE databases, with the last report up to 1 December, 2011. Crude ORs with 95% CIs were used to assess the strength of the association by (1) the additive, (2) the codominant, (3) the dominant, and (4) the recessive models. Results: A total of seven studies, including six studies on FAS -1377G>A polymorphism, five studies on FAS -670A>G polymorphism, and six studies on FASL -844T>C polymorphism, were identified in the current meta-analysis. Overall, an association of FAS -1377G>A (AA versus GG: OR = 1.313, 95% CI = 1.045-1.650, Ph = 0.347, $I^2$ = 10.8) and FASL -844T>C (CC versus TT: OR = 1.352, 95% CI = 1.043-1.752, Ph = 0.461, $I^2$ = 0.0) polymorphisms with gastric cancer was found in the codominant model. However, we did not detect any association between gastric cancer and the FAS -670A>G polymorphism. In the subgroup analysis by ethnicity, similar elevated risks were also observed in Asian population for FAS -1377G>A (AA versus GG: OR = 1.309, 95% CI = 1.041-1.646, Ph = 0.240, $I^2$ = 27.3) and FASL -844T>C (CC versus TT: OR = 1.420, 95% CI = 1.081-1.865, Ph = 0.524, $I^2$ = 0.0) polymorphisms. Conclusions: This meta-analysis indicated that FAS -1377G>A and FASL -844T>C polymorphisms might be associated with gastric cancer risk.

• Korean Journal of Schizophrenia Research
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• v.21 no.2
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• pp.43-50
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• 2018

Objectives : Genome-wide association studies (GWASs) and meta-analyses indicate that single-nucleotide polymorphisms (SNPs) in the a-1C subunit of the L-type voltage-dependent calcium channel (CACNA1C) gene increase the risk for schizophrenia and bipolar disorders (BDs). We investigated the association between the genetic variants on CACNA1C and schizophrenia and/or BDs in the Korean population. Methods : A total of 582 patients with schizophrenia, 336 patients with BDs consisting of 179 bipolar I disorder (BD-I) and 157 bipolar II disorder (BD-II), and 502 healthy controls were recruited. Based on previous results from other populations, three SNPs (rs10848635, rs1006737, and rs4765905) were selected and genotype-wise association was evaluated using logistic regression analysis under additive, dominant and recessive genetic models. Results : rs10848635 showed a significant association with schizophrenia (p=0.010), the combined schizophrenia and BD group (p=0.018), and the combined schizophrenia and BD-I group (p=0.011). The best fit model was dominant model for all of these phenotypes. The association remained significant after correction for multiple testing in schizophrenia and the combined schizophrenia and BD-I group. Conclusion : We identified a possible role of CACNA1C in the common susceptibility of schizophrenia and BD-I. However no association trend was observed for BD-II. Further efforts are needed to identify a specific phenotype associated with this gene crossing the current diagnostic categories.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.1
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• pp.231-236
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• 2013

Background: Published data regarding the association between xeroderma pigmentosum group D (XPD) Lys751Gln and Asp312Asn polymorphisms and gastric cancer susceptibility havew been inconclusive. This meta-analysis was therefore performed toobtain a more precise estimation of any relationship. Materials and Methods: A comprehensive literature search was conducted to identify all case-control studies of Lys751Gln and Asp312Asn polymorphisms and susceptibility to gastric cancer. Summary odds ratios (ORs) and its 95% confidence intervals (95% CIs) were calculated using a random-effects model with the software STATA (version10.0). Results: A total of 12 case-control studies including 3,147 cases and 4,736 controls were included. Overall, no significant associations were found in some models (for Lys751Gln: Lys/Gln vs Lys/Lys: OR=1.144, 95% CI=0.851-1.541, Gln/Gln vs Lys/Lys: OR=1.215, 95% CI = 0.740-1.955, dominant model: OR=1.137, 95% CI=0.818-1.582; recessive model: OR=1.123, 95% CI=0.765-1.650; for Asp312Asn: Asp/Asn vs Asp/Asp: OR=1.180, 95% CI=0.646-2.154, dominant model: OR=1.380, 95% CI = 0.812-2.346), but significantly elevated susceptibility was found for Asp312Asn polymorphism in some models (Asn/Asn vs Asp/Asp: OR=2.045, 95% CI=1.254-3.335, recessive model: OR=1.805, 95% CI =1.219-2.672), for the additive model, the XPD Lys751Gln and Asp312Asn polymorphisms were not significantly associated with gastric cancer susceptibility. In stratified analyses, significantly elevated susceptibility was found for some models in the Chinese population. Conclusion: This meta-analysis suggested the XPD Asp312Asn polymorphism might be a potential biomarker of gastric cancer susceptibility in overall population, while both XPD Lys751Gln and Asp312Asn polymorphisms might be risk factors of gastric cancer susceptibility in Chinese.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.121-142
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• 2023

As the number and weight of imported food are steadily increasing, safety management of imported food to prevent food safety accidents is becoming more important. The Ministry of Food and Drug Safety conducts on-site inspections of foreign food facilities before customs clearance as well as import inspection at the customs clearance stage. However, a data-based safety management plan for imported food is needed due to time, cost, and limited resources. In this study, we tried to increase the efficiency of the on-site inspection by preparing a machine learning prediction model that pre-selects the companies that are expected to fail before the on-site inspection. Basic information of 303,272 foreign food facilities and processing businesses collected in the Integrated Food Safety Information Network and 1,689 cases of on-site inspection information data collected from 2019 to April 2022 were collected. After preprocessing the data of foreign food facilities, only the data subject to on-site inspection were extracted using the foreign food facility_code. As a result, it consisted of a total of 1,689 data and 103 variables. For 103 variables, variables that were '0' were removed based on the Theil-U index, and after reducing by applying Multiple Correspondence Analysis, 49 characteristic variables were finally derived. We build eight different models and perform hyperparameter tuning through 5-fold cross validation. Then, the performance of the generated models are evaluated. The research purpose of selecting companies subject to on-site inspection is to maximize the recall, which is the probability of judging nonconforming companies as nonconforming. As a result of applying various algorithms of machine learning, the Random Forest model with the highest Recall_macro, AUROC, Average PR, F1-score, and Balanced Accuracy was evaluated as the best model. Finally, we apply Kernal SHAP (SHapley Additive exPlanations) to present the selection reason for nonconforming facilities of individual instances, and discuss applicability to the on-site inspection facility selection system. Based on the results of this study, it is expected that it will contribute to the efficient operation of limited resources such as manpower and budget by establishing an imported food management system through a data-based scientific risk management model.

• Journal of Environmental Impact Assessment
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• v.20 no.5
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• pp.747-755
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• 2011

This study was investigated the relationship between the temperature and the mortality of aged (${\geq}65$ yr) during the winter seasons from 1992 to 2007 in Seoul, Korea by utilizing climate data and death records. The study also estimated the future risks by employing the projections of the population in Seoul, Korea and climate change scenario of Korea from 2011 to 2030. The limitation of this study was the impossibility in the prediction of daily mortality counts. Therefore, daily death numbers could be predicted based on the future population projection for Korea and the death records of 2005. The result indicated that risks increased by 0.27%, 0.52%, 0.32% and 0.41% in association with the $1^{\circ}C$ decrease in daily minimum temperature from the mortality counts of total, respiratory, cardiovascular, and cardiorespiratory in the past date while 0.31%, 0.42%, 0.59% and 0.66% in the future. Based on the results obtained from this study, it is concluded that the risk in the future will be higher than the past date although there is an uncertainty in estimating death counts in the future.

• Journal of Preventive Medicine and Public Health
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• v.39 no.1
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• pp.81-86
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• 2006

Background: A number of studies have reported associations between the ambient air pollution concentrations and various health outcomes. Especially, ozone is well known for primary risk factor of asthma attacks. The results of a recent study indicate that the size of the effect on health outcomes due to air pollution varied according to several conditions, including age, gender, race and the socioeconomic status. Therefore, this study was conducted to examine the associations of ozone with the childhood asthma hospitalizations as stratified by the socioeconomic status (SES) at the community level in Seoul, Korea, 2002. Methods: SES at aggregated levels was measured on the basis of average regional health-insurance rate per citizen in the area. We applied the generalized additive model to analyze the effect of ozone on asthma after controlling for the potential confounding variables that were capable of influencing the results. Results: Our analysis showed that the number of children who were hospitalized for asthma increased as the SES of the residence area decreased. The estimated relative risks of hospitalization for asthma, as stratified by the SES of the community level, were 1.12 (95% confidence interval 1.00-1.25) in districts with the highest SES levels, 1.24 (95% CI=1.08-1.43) within the moderate SES levels, and 1.32 (95% CI=1.11-1.58) in the districts with the lowest SES levels. Conclusions: Our analysis showed that exposure to air pollution did not equally affect the health status of individuals. This suggests that not only the biological-sensitivity markers, but also the SES of the subjects should be considered as potentially confounding factors.

• Journal of Trauma and Injury
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• v.37 no.3
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• pp.201-208
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• 2024

Purpose: The number of elderly patients with trauma is increasing; therefore, precise models are necessary to estimate the mortality risk of elderly patients with trauma for informed clinical decision-making. This study aimed to develop machine learning based predictive models that predict 30-day mortality in severely injured elderly patients with trauma and to compare the predictive performance of various machine learning models. Methods: This study targeted patients aged ≥65 years with an Injury Severity Score of ≥15 who visited the regional trauma center at Chungbuk National University Hospital between 2016 and 2022. Four machine learning models-logistic regression, decision tree, random forest, and eXtreme Gradient Boosting (XGBoost)-were developed to predict 30-day mortality. The models' performance was compared using metrics such as area under the receiver operating characteristic curve (AUC), accuracy, precision, recall, specificity, F1 score, as well as Shapley Additive Explanations (SHAP) values and learning curves. Results: The performance evaluation of the machine learning models for predicting mortality in severely injured elderly patients with trauma showed AUC values for logistic regression, decision tree, random forest, and XGBoost of 0.938, 0.863, 0.919, and 0.934, respectively. Among the four models, XGBoost demonstrated superior accuracy, precision, recall, specificity, and F1 score of 0.91, 0.72, 0.86, 0.92, and 0.78, respectively. Analysis of important features of XGBoost using SHAP revealed associations such as a high Glasgow Coma Scale negatively impacting mortality probability, while higher counts of transfused red blood cells were positively correlated with mortality probability. The learning curves indicated increased generalization and robustness as training examples increased. Conclusions: We showed that machine learning models, especially XGBoost, can be used to predict 30-day mortality in severely injured elderly patients with trauma. Prognostic tools utilizing these models are helpful for physicians to evaluate the risk of mortality in elderly patients with severe trauma.

• Korean Journal of Clinical Pharmacy
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• v.21 no.4
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• pp.364-375
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• 2011

Given that single blockade with angiotensin-converting enzyme inhibitors (ACEIs) or angiotensin receptor blockers (ARBs) can achieve only partial and undurable suppression of the Renin Angiotensin System (RAS), it has been hypothesized that dual blockage would be more beneficial in the management of blood pressure (BP) reduction and prevention of progressive chronic kidney disease (CKD) than either agent alone. Thus, it has been suggested that the combination of an ACEI and an ARB might provide renal benefits to hypertensive patients over and above BP reduction. However, this might also expose patients to additive or synergistic side effects. We attempted to conduct a systematic review to evaluate the benefits and harms of combination therapy in hypertensive patients with or without kidney diseases. MEDLINE and KoreaMed were searched for relevant randomized clinical trials in adult hypertensive patients with or without diabetes (restricted to 1997, limited to trials published in English). Results were summarized using the random-effects model, and between-studies heterogeneity was estimated with $I^2$. A final analysis of ten trials (23,928 patients) revealed that the combination of an ACEI and an ARB reduced blood pressure (SBP/DBP) by 3.95/2.02 mmHg (95% confidence interval [CI], -4.38 to -3.53/-2.33 to -1.71) compared with ACEI monotherapy, and 2.83/2.64 mmHg (95% CI, -3.25 to -2.41/-4.95 to -0.33) compared with ARB monotherapy. Eight trials (391 patients) demonstrated a significant reduction in 24h-proteinuria (weighted mean difference, 0.16 g/day, 95% CI, -0.26-0.05), but they did not translate into an improvement in GFR. Tests for heterogeneity showed no difference in effect among the studies. The combination therapy reduced proteinuria by 30% (95% CI, 23% to 37%) and 39% (95% CI, 31% to 48%) compared with ACEI monotherapy and ARB monotherapy, respectively. However, in patients who had proteinuria more than 0.5 g/day, the combination therapy failed to show significant reduction in urinary protein excretion. The current cumulative evidence suggests that diabetic patients with proteinuria on dual RAS blockade have an increase risk of adverse events such as hyperkalemia, hypotension, and so on, compared with ACEI or ARB alone. It is, therefore, proposed that the combination therapy should not be routinely used for the treatment of hypertension with or without compelling indications.

• Journal of the Korean Child Neurology Society
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• v.26 no.4
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• pp.227-232
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• 2018

Purpose: Febrile seizure (FS) is the most common type of seizure in children between 6 months to 5 years of age. A family history of febrile seizures can increase the risk a child will have a FS. Yet, prevalence of FS regarding external environment has not been clearly proved. This study attempts to determine the association between prevalence of FS and weather. Methods: This study included medical records from the Korea National Health Insurance Review and Assessment Service. Data were collected from 29,240 children, born after 2004, diagnosed with FS who were admitted to one of the hospitals in Seoul, Korea, between January 2009 and December 2013. During the corresponding time period, data from the Korea Meteorological Administration on daily monitoring of four meteorological factors (sea-level pressure, amount of precipitation, humidity and temperature) were collected. The relationships of FS prevalence and each meteorological factor will be designed using Poisson generalized additive model (GAM). Also, the contributory effect of viral infections on FS prevalence and weather will be discussed. Results: The amount of precipitation was divided into two groups for comparison: one with less than 5 mm and the other with equal to or more than 5 mm. As a result of Poisson GAM, higher prevalence of FS showed a correlation with smaller amount of precipitation. Smoothing function was used to classify the relationships between three variables (sea-level pressure, humidity, and temperature) and prevalence of FS. FS prevalence was correlated with lower sea-level pressure and lower humidity. FS prevalence was high in two temperature ranges (-7 to $-1^{\circ}C$ and $18-21^{\circ}C$). Conclusion: Low sea-level pressure, small amount of precipitation, and low relative air humidity may increase FS prevalence risk.